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Scott E. Page
We live in a complex world with diverse people, firms, and governments whose behaviors aggregate to produce novel, unexpected phenomena. We see political uprisings, market crashes, and a never ending array of social trends. How do we make sense of it? Models. Evidence shows that people who think with models consistently outperform those who don't. And, moreover people who think with lots of models outperform people who use only one. Why do models make us better thinkers? Models help us to better organize information - to make sense of that fire hose or hairball of data (choose your metaphor) available on the Internet. Models improve our abilities to make accurate forecasts. They help us make better decisions and adopt more effective strategies. They even can improve our ability to design institutions and procedures. In this class, I present a starter kit of models: I start with models of tipping points. I move on to cover models explain the wisdom of crowds, models that show why some countries are rich and some are poor, and models that help unpack the strategic decisions of firm and politicians.
Read more
We live in a complex world with diverse people, firms, and governments whose behaviors aggregate to produce novel, unexpected phenomena. We see political uprisings, market crashes, and a never ending array of social trends. How do we make sense of it? Models. Evidence shows that people who think with models consistently outperform those who don't. And, moreover people who think with lots of models outperform people who use only one. Why do models make us better thinkers? Models help us to better organize information - to make sense of that fire hose or hairball of data (choose your metaphor) available on the Internet. Models improve our abilities to make accurate forecasts. They help us make better decisions and adopt more effective strategies. They even can improve our ability to design institutions and procedures. In this class, I present a starter kit of models: I start with models of tipping points. I move on to cover models explain the wisdom of crowds, models that show why some countries are rich and some are poor, and models that help unpack the strategic decisions of firm and politicians.
Read more
We live in a complex world with diverse people, firms, and governments whose behaviors aggregate to produce novel, unexpected phenomena. We see political uprisings, market crashes, and a never ending array of social trends. How do we make sense of it? Models. Evidence shows that people who think with models consistently outperform those who don't. And, moreover people who think with lots of models outperform people who use only one. Why do models make us better thinkers? Models help us to better organize information - to make sense of that fire hose or hairball of data (choose your metaphor) available on the Internet. Models improve our abilities to make accurate forecasts. They help us make better decisions and adopt more effective strategies. They even can improve our ability to design institutions and procedures. In this class, I present a starter kit of models: I start with models of tipping points. I move on to cover models explain the wisdom of crowds, models that show why some countries are rich and some are poor, and models that help unpack the strategic decisions of firm and politicians.
The models covered in this class provide a foundation for future social science classes, whether they be in economics, political science, business, or sociology. Mastering this material will give you a huge leg up in advanced courses. They also help you in life. Here's how the course will work. For each model, I present a short, easily digestible overview lecture. Then, I'll dig deeper. I'll go into the technical details of the model. Those technical lectures won't require calculus but be prepared for some algebra. For all the lectures, I'll offer some questions and we'll have quizzes and even a final exam. If you decide to do the deep dive, and take all the quizzes and the exam, you'll receive a Course Certificate. If you just decide to follow along for the introductory lectures to gain some exposure that's fine too. It's all free. And it's all here to help make you a better thinker!
Register for this course and see more details by visiting:
OpenCourser.com/course/71uuue/model
What's inside
Syllabus
Why Model & Segregation/Peer Effects
In these lectures, I describe some of the reasons why a person would want to take a modeling course. These reasons fall into four broad categories: 1)To be an intelligent citizen of the world 2) To be a clearer thinker 3) To understand and use data 4) To better decide, strategize, and design. There are two readings for this section. These should be read either after the first video or at the completion of all of the videos.We now jump directly into some models. We contrast two types of models that explain a single phenomenon, namely that people tend to live and interact with people who look, think, and act like themselves. After an introductory lecture, we cover famous models by Schelling and Granovetter that cover these phenomena. We follows those with a fun model about standing ovations that I wrote with my friend John Miller.
Read more
Syllabus
Why Model & Segregation/Peer Effects
In these lectures, I describe some of the reasons why a person would want to take a modeling course. These reasons fall into four broad categories: 1)To be an intelligent citizen of the world 2) To be a clearer thinker 3) To understand and use data 4) To better decide, strategize, and design. There are two readings for this section. These should be read either after the first video or at the completion of all of the videos.We now jump directly into some models. We contrast two types of models that explain a single phenomenon, namely that people tend to live and interact with people who look, think, and act like themselves. After an introductory lecture, we cover famous models by Schelling and Granovetter that cover these phenomena. We follows those with a fun model about standing ovations that I wrote with my friend John Miller.
Read more
Aggregation & Decision Models
In this section, we explore the mysteries of aggregation, i.e. adding things up. We start by considering how numbers aggregate, focusing on the Central Limit Theorem. We then turn to adding up rules. We consider the Game of Life and one dimensional cellular automata models. Both models show how simple rules can combine to produce interesting phenomena. Last, we consider aggregating preferences. Here we see how individual preferences can be rational, but the aggregates need not be.There exist many great places on the web to read more about the Central Limit Theorem, the Binomial Distribution, Six Sigma, The Game of Life, and so on. I've included some links to get you started. The readings for cellular automata and for diverse preferences are short excerpts from my books Complex Adaptive Social Systems and The Difference Respectively.
Thinking Electrons: Modeling People & Categorical and Linear Models
In this section, we study various ways that social scientists model people. We study and contrast three different models. The rational actor approach, behavioral models, and rule based models . These lectures provide context for many of the models that follow. There's no specific reading for these lectures though I mention several books on behavioral economics that you may want to consider. Also, if you find the race to the bottom game interesting just type "Rosemary Nagel Race to the Bottom" into a search engine and you'll get several good links. You can also find good introductions to "Zero Intelligence Traders" by typing that in as well.
Tipping Points & Economic Growth
In this section, we cover tipping points. We focus on two models. A percolation model from physics that we apply to banks and a model of the spread of diseases. The disease model is more complicated so I break that into two parts. The first part focuses on the diffusion. The second part adds recovery. The readings for this section consist of two excerpts from the book I'm writing on models. One covers diffusion. The other covers tips. There is also a technical paper on tipping points that I've included in a link. I wrote it with PJ Lamberson and it will be published in the Quarterly Journal of Political Science. I've included this to provide you a glimpse of what technical social science papers look like. You don't need to read it in full, but I strongly recommend the introduction. It also contains a wonderful reference list.
Diversity and Innovation & Markov Processes
In this section, we cover some models of problem solving to show the role that diversity plays in innovation. We see how diverse perspectives (problem representations) and heuristics enable groups of problem solvers to outperform individuals. We also introduce some new concepts like "rugged landscapes" and "local optima". In the last lecture, we'll see the awesome power of recombination and how it contributes to growth. The readings for this chapters consist on an excerpt from my book The Difference courtesy of Princeton University Press.
Midterm Exam
Lyapunov Functions & Coordination and Culture
Models can help us to determine the nature of outcomes produced by a system: will the system produce an equilibrium, a cycle, randomness, or complexity? In this set of lectures, we cover Lyapunov Functions. These are a technique that will enable us to identify many systems that go to equilibrium. In addition, they enable us to put bounds on how quickly the equilibrium will be attained. In this set of lectures, we learn the formal definition of Lyapunov Functions and see how to apply them in a variety of settings. We also see where they don't apply and even study a problem where no one knows whether or not the system goes to equilibrium or not.
Path Dependence & Networks
In this set of lectures, we cover path dependence. We do so using some very simple urn models. The most famous of which is the Polya Process. These models are very simple but they enable us to unpack the logic of what makes a process path dependent. We also relate path dependence to increasing returns and to tipping points. The reading for this lecture is a paper that I wrote that is published in the Quarterly Journal of Political Science
Randomness and Random Walks & Colonel Blotto
In this section, we first discuss randomness and its various sources. We then discuss how performance can depend on skill and luck, where luck is modeled as randomness. We then learn a basic random walk model, which we apply to the Efficient Market Hypothesis, the ideas that market prices contain all relevant information so that what's left is randomness. We conclude by discussing finite memory random walk model that can be used to model competition. The reading for this section is a paper on distinguishing skill from luck by Michael Mauboussin.
Prisoners' Dilemma and Collective Action & Mechanism Design
In this section, we cover the Prisoners' Dilemma, Collective Action Problems and Common Pool Resource Problems. We begin by discussion the Prisoners' Dilemma and showing how individual incentives can produce undesirable social outcomes. We then cover seven ways to produce cooperation. Five of these will be covered in the paper by Nowak and Sigmund listed below. We conclude by talking about collective action and common pool resource problems and how they require deep careful thinking to solve. There's a wonderful piece to read on this by the Nobel Prize winner Elinor Ostrom.
Learning Models: Replicator Dynamics & Prediction and the Many Model Thinker
In this section, we cover replicator dynamics and Fisher's fundamental theorem. Replicator dynamics have been used to explain learning as well as evolution. Fisher's theorem demonstrates how the rate of adaptation increases with the amount of variation. We conclude by describing how to make sense of both Fisher's theorem and our results on six sigma and variation reduction. The readings for this section are very short. The second reading on Fisher's theorem is rather technical. Both are excerpts from Diversity and Complexity.
Final Exam
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Uses models to provide a foundation for future social science classes, such as economics, political science, business, or sociology
Guides through models that help learners better organize and understand information
Enhances learners' abilities to make accurate forecasts and adopt more effective strategies
Provides a starter kit of models that explain topics like tipping points, the wisdom of crowds, and the wealth of nations
Models are easily digestible and accessible, ensuring a smooth learning experience
Save this course
Save Model Thinking to your list so you can find it easily later:
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Reviews summary
Well-received course on model thinking
Learners say Model Thinking is a well-received course that provides a great introduction to the basics of model thinking. Excellent lectures are delivered by an enthusiasticenthusiastic instructor, and the course content is engaging and relevant for those interested in learning about models. Overall, learners say this course is highly recommended for anyone looking to expand their knowledge of model thinking.
Learners find the course relevant and applicable to real-life situations.
"I'm currently taking this class and really enjoying it. [...] I enjoy how ideas from many different fields are stitched together."
"Very useful insight on model approach to different situation .. help understand the world with the eyes of statistics logic and maths. Very straightforward!!"
Learners appreciate the wide variety of models covered in the course.
"It covers a variety of models. Useful to gain a basic understanding of each of them. Good examples in Netscape software."
"The way the course touches each subject lightly is fine for me. The wide variety of models described, the examples given and the way the theory is explained is well executed."
Learners appreciate the well-taught and entertaining lectures.
"Very well taught by an enthusiastic and entertaining teacher. I learned a lot and would be excited about any available follow up."
"Great introduction to the world of scientific modelling without ever becoming boring. Great for all subjects. Gifted lecturer, great mix of tools (videos, experiments, examples). One of lasting impact."
Some learners note that the course lacks depth due to the breadth of topics covered.
"This was a great course and I learned a great deal out of it. [...] I would recommend it to others interested in learning a wide range of models that they can apply to a ton of thought experiments or real-life situations."
"Great course. It opened my mind to many new ideas that I didn't knew existed. The topics are so varied that unfortunately the contents don't have much depth, but Dr. Page teaches you just enough for you to start learning on your own about whatever topic picked your interest. Highly recommended!"
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Model Thinking with these
activities:
Review basic probability and statistics concepts
Show steps
Probability and statistics are essential for understanding many of the models covered in this course. Review these concepts before starting the course to refresh your memory and improve your understanding.
Browse courses on
Probability
Show steps
-
Review your notes or textbooks from a previous probability and statistics course
-
Take a practice quiz or exam to test your understanding
Review lecture notes and readings from a previous course on social science modeling
Show steps
If you have taken a previous course on social science modeling, review the lecture notes and readings to refresh your memory on the key concepts.
Browse courses on
Agent-Based Modeling
Show steps
-
Gather your lecture notes and readings from the previous course
-
Review the material and take notes as needed
Gather and organize course materials
Show steps
Start building a library of materials that you can use to study, review, and practice for the course.
Show steps
-
Set up a filing system for notes, assignments, and other handouts
-
Scan or take photos of important documents
-
Create a digital or physical library of reference materials, such as textbooks, articles, and videos
Six other activities
Expand to see all activities and additional details
Show all nine activities
Join a study group or discussion forum
Show steps
Joining a study group or discussion forum can provide you with opportunities to discuss the course material with other students, ask questions, and get help with difficult concepts.
Show steps
-
Find a study group or discussion forum related to the course
-
Introduce yourself and participate in the discussions
Use online tutorials to learn about Markov processes
Show steps
Markov processes are used to model a wide variety of phenomena, from the spread of diseases to the behavior of financial markets. Use online tutorials to learn more about Markov processes.
Browse courses on
Markov Processes
Show steps
-
Find a set of online tutorials on Markov processes
-
Follow the tutorials and complete the associated exercises
Read 'Complex Adaptive Social Systems' by Scott E. Page
Show steps
This book covers a broad range of topics relevant to the course, including models of social networks, segregation, and collective behavior.
View
Diversity and Complexity
on Amazon
Show steps
-
Read the book and take notes
-
Summarize the key concepts in your own words
-
Identify the connections between the book and the course material
Practice solving tipping point problems
Show steps
Tipping points are common in many social and economic systems. Practice solving problems related to tipping points to improve your understanding of the concept.
Browse courses on
Tipping Points
Show steps
-
Find a set of practice problems related to tipping points
-
Solve the problems using the methods learned in the course
-
Check your solutions against the provided answer key
Build a model of a social or economic system
Show steps
Build a model of a social or economic system to apply the concepts learned in the course and gain a deeper understanding of how these systems work.
Show steps
-
Choose a social or economic system to model
-
Identify the key variables and relationships in the system
-
Develop a mathematical or computational model of the system
-
Simulate the model to generate data
-
Analyze the data to draw conclusions about the system
Write a blog post or article about a topic covered in the course
Show steps
Writing about a topic helps you to solidify your understanding and identify areas where you need further study. Choose a topic that you find particularly interesting or challenging and write a blog post or article about it.
Show steps
-
Choose a topic related to the course material
-
Research the topic to gather information
-
Organize your thoughts and write an outline
-
Write the blog post or article
Review basic probability and statistics concepts
Show steps
Probability and statistics are essential for understanding many of the models covered in this course. Review these concepts before starting the course to refresh your memory and improve your understanding.
Browse courses on
Probability
Show steps
Show steps
Show steps
- Review your notes or textbooks from a previous probability and statistics course
- Take a practice quiz or exam to test your understanding
Review lecture notes and readings from a previous course on social science modeling
Show steps
If you have taken a previous course on social science modeling, review the lecture notes and readings to refresh your memory on the key concepts.
Browse courses on
Agent-Based Modeling
Show steps
Show steps
Show steps
- Gather your lecture notes and readings from the previous course
- Review the material and take notes as needed
Gather and organize course materials
Show steps
Start building a library of materials that you can use to study, review, and practice for the course.
Show steps
Show steps
Show steps
- Set up a filing system for notes, assignments, and other handouts
- Scan or take photos of important documents
- Create a digital or physical library of reference materials, such as textbooks, articles, and videos
Six other activities
Expand to see all activities and additional details
Show all nine activities
Join a study group or discussion forum
Show steps
Joining a study group or discussion forum can provide you with opportunities to discuss the course material with other students, ask questions, and get help with difficult concepts.
Show steps
Show steps
Show steps
- Find a study group or discussion forum related to the course
- Introduce yourself and participate in the discussions
Use online tutorials to learn about Markov processes
Show steps
Markov processes are used to model a wide variety of phenomena, from the spread of diseases to the behavior of financial markets. Use online tutorials to learn more about Markov processes.
Browse courses on
Markov Processes
Show steps
Show steps
Show steps
- Find a set of online tutorials on Markov processes
- Follow the tutorials and complete the associated exercises
Read 'Complex Adaptive Social Systems' by Scott E. Page
Show steps
This book covers a broad range of topics relevant to the course, including models of social networks, segregation, and collective behavior.
View
Diversity and Complexity
on Amazon
Show steps
Show steps
Show steps
- Read the book and take notes
- Summarize the key concepts in your own words
- Identify the connections between the book and the course material
Practice solving tipping point problems
Show steps
Tipping points are common in many social and economic systems. Practice solving problems related to tipping points to improve your understanding of the concept.
Browse courses on
Tipping Points
Show steps
Show steps
Show steps
- Find a set of practice problems related to tipping points
- Solve the problems using the methods learned in the course
- Check your solutions against the provided answer key
Build a model of a social or economic system
Show steps
Build a model of a social or economic system to apply the concepts learned in the course and gain a deeper understanding of how these systems work.
Show steps
Show steps
Show steps
- Choose a social or economic system to model
- Identify the key variables and relationships in the system
- Develop a mathematical or computational model of the system
- Simulate the model to generate data
- Analyze the data to draw conclusions about the system
Write a blog post or article about a topic covered in the course
Show steps
Writing about a topic helps you to solidify your understanding and identify areas where you need further study. Choose a topic that you find particularly interesting or challenging and write a blog post or article about it.
Show steps
Show steps
Show steps
- Choose a topic related to the course material
- Research the topic to gather information
- Organize your thoughts and write an outline
- Write the blog post or article
Career center
Learners who complete Model Thinking will develop knowledge and skills
that may be useful to these careers:
Market Researcher
Market Researcher
Market Researchers collect and analyze data about consumers and markets, using models to draw conclusions about consumer behavior, trends, and demand. By using the models and datasets learned in Model Thinking, you will be well prepared to effectively carry out these duties. Model Thinking will also help you to make accurate forecasts, design effective strategies, and contribute to the decision-making process.
Financial Analyst
Financial Analyst
Financial Analysts use data and financial models to help businesses and investors with financial planning and decision-making. Model Thinking will provide you with the tools you need to make accurate forecasts, identify trends and patterns, and develop sound investment strategies.
Data Scientist
Data Scientist
Data Scientists use models to analyze data and extract insights. Model Thinking will provide you with the tools you need to develop and analyze models, and to communicate your findings to stakeholders.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts develop and use mathematical and statistical models to analyze data and solve problems in finance. Model Thinking will help you to build a strong foundation in modeling, data analysis, and problem solving. The course will also equip you with the skills you need to communicate your findings to non-technical audiences.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use models to develop and implement machine learning algorithms. Model Thinking will provide you with the tools you need to develop and analyze machine learning models, and to build and deploy machine learning systems.
Data Analyst
Data Analyst
Data Analysts use statistical methods to collect, analyze, interpret and present data, most often to support decision-making. Model Thinking will provide you a comprehensive understanding of models, data interpretation and presentation. The course will also give you the ability to identify and present insights from data.
Political Scientist
Political Scientist
Political Scientists use models to analyze political phenomena, such as voting behavior and public policy. Model Thinking will provide you with the tools you need to develop and analyze political models, and to understand the impact of political decisions.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve problems in a variety of industries, including manufacturing, transportation, and healthcare. Model Thinking will provide you with the tools you need to develop and analyze models, and to make recommendations for improving operations.
Economist
Economist
Economists use economic models to analyze economic data and make predictions about the economy. Model Thinking will provide you with the tools you need to develop and analyze economic models, and to understand the impact of economic policies.
Business Analyst
Business Analyst
Business Analysts use data and models to analyze and improve business processes and systems. Model Thinking will help you to develop the skills you need to model complex systems, identify inefficiencies, and develop solutions. The course will also give you the ability to communicate your findings to business stakeholders.
Social Scientist
Social Scientist
Social Scientists use models to analyze social phenomena, such as crime, poverty, and education. Model Thinking will provide you with the tools you need to develop and analyze social models, and to understand the impact of social policies.
Systems Analyst
Systems Analyst
Systems Analysts use models to analyze and design systems, such as computer systems and business processes. Model Thinking will provide you with the tools you need to develop and analyze system models, and to make recommendations for improving system performance.
Software Engineer
Software Engineer
Software Engineers use models to design and develop software programs. Model Thinking will provide you with the tools you need to develop and analyze software models, and to write efficient and reliable code.
Product Manager
Product Manager
Product Managers use models to analyze market data and customer feedback to develop and improve products. Model Thinking will provide you with the tools you need to develop and analyze product models, and to make decisions about product development and marketing.
Management Consultant
Management Consultant
Management Consultants use analytical and problem-solving skills to help organizations improve their performance. Model Thinking will help you to develop the skills you need to analyze complex problems, develop solutions, and implement change. The course will also give you the ability to communicate your findings to clients.
For more career information including salaries, visit:
OpenCourser.com/course/71uuue/model
Reading list
We've selected 15 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Model Thinking.
Save
Is by the same professor who teaches this course. It provides additional context for some of the models covered in the course, such as the Schelling model of segregation.
Save
Is also by the same professor who teaches this course. It provides additional context for some of the models covered in the course, such as the Schelling model of segregation.
Save
Provides a general introduction to model thinking. It covers a wide range of topics, including how to identify the right model, how to build a model, and how to use models to make decisions.
Classic work on bounded rationality. It provides a theoretical framework for understanding how people make decisions in the face of limited information and cognitive constraints.
Save
Explores the irrational side of human behavior. It provides a number of examples of how people make irrational decisions, and it discusses the factors that contribute to these irrationalities.
Save
Explores the role of habits in our lives. It provides a number of examples of how habits can shape our behavior, and it discusses the strategies that we can use to change our habits.
Explores the factors that contribute to the success of ideas, products, and movements. It provides a number of examples of how ideas have spread rapidly, and it discusses the strategies that we can use to create our own tipping points.
Provides a broad overview of human history. It covers a wide range of topics, including the origins of our species, the development of agriculture, the rise of cities, and the emergence of modern society.
Save
Provides a history of the gene. It covers a wide range of topics, including the discovery of DNA, the development of genetic engineering, and the ethical implications of genetic research.
Explores the current extinction crisis. It provides a number of examples of how human activity is driving the extinction of other species, and it discusses the consequences of this extinction for the planet.
Save
Explores the psychological and cultural barriers to addressing climate change. It argues that we need to change the way we think about climate change if we want to take effective action to address it.
Save
Explores the relationship between humans and the natural world. It provides a number of examples of how indigenous cultures have lived in harmony with the land, and it discusses the lessons that we can learn from these cultures.
Explores the factors that contribute to the collapse of societies. It provides a number of examples of how societies have collapsed in the past, and it discusses the lessons that we can learn from these collapses.
Explores the factors that contribute to economic growth. It argues that free markets and individual liberty are the key to prosperity, and it provides a number of examples of how these principles have led to economic growth in the past.
Save
Explores the paradox of progress. It argues that while life has gotten better in many ways, we often feel worse off because we compare ourselves to others and because we are constantly bombarded with negative news.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/71uuue/model
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Effort
4-8 hours/week
Level
Intermediate
Via
Coursera
Institution
University of Michigan
Instructor
Scott E. Page
Language
English
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Good to know
Uses models to provide a foundation for future social science classes, such as economics, political science, business, or sociology
Guides through models that help learners better organize and understand information
Enhances learners' abilities to make accurate forecasts and adopt more effective strategies
Provides a starter kit of models that explain topics like tipping points, the wisdom of crowds, and the wealth of nations
Models are easily digestible and accessible, ensuring a smooth learning experience
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